基于特征融合一维卷积神经网络的电能质量扰动分类

现有基于特征选取的电能质量扰动分类算法存在鲁棒性差、抗噪性能不强等问题。提出了一种改进的一维卷积神经网络用于电能质量扰动信号的分类。首先通过三个卷积神经网络子模型分别提取电能质量扰动信号的特征向量,然后将提取的特征向量融合为一个新的特征向量,最后通过BP神经网络实现分类。与改进前的一维卷积神经网络模型以及现有的电能质量扰动分类算法相比,该算法提取的特征向量具有更大的区分度。仿真结果表明,该算法有更好的鲁棒性和识别率,且抗噪能力强,为电能质量扰动信号分类提供了一种新思路。     

基于业务的电力通信网络脆弱性分析评价方法

为解决传统复杂网络理论脆弱性分析的局限性并改善网络性能,提出了一种基于业务的电力通信网络脆弱性分析方法。利用复杂网络理论构建网络模型,将业务重要度和业务流量作为网络参数,在蓄意攻击和随机攻击的策略下,以链路或节点失效所造成的业务量损失大小来描述网络的脆弱性,并找出网络中相应的脆弱部位。以电力IEEE30节点测试系统作为仿真实例,结果表明,网络业务分布越不均匀,网络脆弱性就会越高,进而网络抵御级联故障的能力就越差。而且在蓄意攻击的情况下,网络脆弱性极高。得出结论,网络业务分布越均匀,网络脆弱性就会越低。针对结论,提出了改进业务路由策略的方法以降低网络的脆弱性。仿真证明了该方法的有效性和可用性,并可为电力通信网络规划和维护提供参考,具有现实意义。     

基于快速近似联合对角化的谐波发射水平评估方法

提出了一种基于快速近似联合对角化(FAJD)估计系统谐波阻抗及计算谐波发射水平的新方法。在直角坐标下,根据谐波诺顿等效电路的基本原理,推导得出公共连接点处谐波电压和电流与系统和用户侧谐波电流源的关系。考虑两侧谐波电流源相互独立的基本条件,利用FAJD方法求得解混矩阵并分离出两侧谐波电流源分量,采用最小二乘法求得混合系数矩阵,对比基本电路方程求得系统侧谐波阻抗的实部和虚部,进而评估谐波发射水平。该方法以公共连接点测量的谐波电压和电流信息为基础,无需先验数据匹配也不要求目标观测矩阵为正交矩阵,因此无需预白化处理,避免引入不必要的误差,具有更高的分离精度和更强的抗背景谐波干扰能力。最后,通过仿真对比分析与实测数据验证了所提方法的可行性和有效性。     

考虑重构的含可再生能源配电网电压控制模型与算法

风电、光伏等分布式电源高渗透并入10kV中压配电网,将导致系统运行经济性与电压质量等问题,若不加以有效管控,则难以充分消纳可再生能源。为实现可再生能源接入下配电网电压安全的主动管控,提出兼顾配电网结构灵活性与电压调节资源能力的机会约束双层优化模型。模型上层以配电网动态重构为手段,确保长时间尺度内的经济运行原则;下层以馈线自动调压器控制策略为对象,实现局部支路电压水平优化。为提高算法效率,利用二阶锥法松弛潮流约束,并采用库恩—塔克(KKT)条件将模型等效转化为单层决策模型。算例结果表明,所提方法通过主动重构技术协调局部电压调节资源,可实现可再生能源接入下配电网的电压安全运行控制。     

Optimal capacity design of battery and hydrogen system for the DC grid with photovoltaic power generation based on the rapid estimation of grid dependency

This paper presents a fast and novel method to determine the optimal capacity of a battery and a hydrogen system for a grid-connected photovoltaic (PV) system based on the required grid dependency (GD) and the minimum Levelized Cost of Energy (LCE). The GD is calculated from the weather data at 9 locations throughout Japan during 25 years considering different sizing of PV, battery, and hydrogen system. Based on the results, the relationship between the GD and the capacities of the devices and the weather parameter is established. The results show that the GD depends on the annual total solar insolation and the devices’ capacities as well. The empirical GD formula is then examined at a different location in Japan. The proposed GD calculation agrees well with the GD obtained from the real 25 – year weather data and shows great advantages over the conventional method in the simplicity and calculation time. In addition, the optimal capacity of the system can be obtained directly from the GD formula and the objective function of the LCE.     

The rational approximations of the unitary groups

This paper is to investigate the rational approximation of the unitary groups. Specially, based on the Household decomposition we prove that the rational unitary subgroup is dense in the complex unitary group. Moreover, its random approximate property is characterized by the natural Harr measure, which can be used to obtain random unitary matrix. Our simulation shows that these results may be applied to approximate quantum computations.     

Type-3 fuzzy voltage management in PV/Hydrogen fuel cell/battery hybrid systems

In this paper a novel strategy using type-3 (T3) fuzzy logic systems (FLSs) is designed for voltage management in the hybrid systems that include photovoltaic, battery and hydrogen fuel cells (FC). The stability and robustness are proved in the versus of time-variable irradiation, temperature and output load. The suggested T3-FLS is learned by tuning laws that are concluded form robustness analysis. The effects of perturbations and estimation errors are compensated by the schemed controller such that a good regulation performance to be achieved. The performance of the suggested technique is examined under challenging conditions such as time-variable and unknown dynamics, variable irradiation, variable temperature and abruptly changes in output load. Comparison with classic management methods show that the suggested approach results in better regulation performance, in the circumstances that, unlike to the compared methods, the mathematical dynamics of all units are assumed to be unknown.     

Decision trees aided scheduling for firm power capacity provision by virtual power plants

The incorporation of Distributed Generation (DG) under the Virtual Power Plant (VPP) concept allows the market integration of several and largely dispersed electric power sources. One matter of concern for the VPP owner and operator is to follow the hourly schedule regardless of the stochastic nature of some of its sources or any unpredicted generation outages. This study presents a Decision Tree (DT) based methodology that prepares for the dispatching of power equivalent to the possible loss of the highest injection of one of the sources of the VPP (according to day-ahead hourly schedule) to the rest of its sources, on an hour-ahead horizon. This allows VPP operators to provide firm capacity and participate effectively in the energy market.     

基于行波模量速度差的配电网故障测距迭代算法

提出了基于零模检测波速度与故障距离关系曲线的配电网故障测距迭代算法。针对零模检测波速度随故障距离变化较大的问题,通过分析及仿真发现了零模检测波速度随故障距离的变化规律,利用该规律给出了零模检测波速度的距离表达式。将此表达式结合基于零模行波分量和线模行波分量速度差的测距公式,给出了故障测距的迭代算法,避免了零模波速度难以确定的问题。通过ATP及Matlab对该算法进行仿真,仿真结果证实了该方法的有效性和可靠性。     

电力波分复用网络中基于软管模型的生存性设计

生存性设计是规划电力通信波分复用(WDM)网络时必须考虑的问题。传统的方法根据各节点对的峰值速率来制定保护规划方案,也并未考虑光纤链路之间共享物理资源的情况,既不准确又浪费资源。为解决上述问题,提出了一种新的计算共享风险链路组的失效概率模型,并以此为基础,提出了基于软管不确定业务量模型和共享风险链路组的分级保护算法——HSP算法,并通过计算机仿真对该算法的性能进行了评估。结果表明,HSP显著提高了找到保护路径的可能性,从而降低了受损业务无法恢复的概率。失效概率模型和HSP算法还应用到了某省级电力波分复用核心网络的成效评估和规划设计中,作为评估该省电力骨干光传输网络建设成本和可靠性的依据。